Accession Number:

ADA093633

Title:

Smoothing Estimation of Stochastic Processes. Part I. Change of Initial Condition Formulae.

Descriptive Note:

Technical summary rept.,

Corporate Author:

WISCONSIN UNIV-MADISON MATHEMATICS RESEARCH CENTER

Personal Author(s):

Report Date:

1980-09-01

Pagination or Media Count:

35.0

Abstract:

Recently a great amount of attention has been focused on various algorithms for solving the smoothing problem of linear estimation theory. This work is the first part of a two part investigation of these algorithms. In Part I it is shown how change of initial condition CIC or partitioning formulae hold in a very general setting the CIC problem is shown to involve fixed rank perturbation in matrix inversion. In Part II the nature of the two-filter algorithms is explored by providing a simple derivation that shows to what extent the formulae hold generally and so reveals exactly how a wide sense Markovian assumption is necessary for their full utility. The remainder of the paper is structured as follows. Section I contains a discussion of CIC formulae for discrete observations. Section II concerns CIC formulae for continuous observations actually the formulae are the same. Section III discusses the relation with other work.

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE